Enterprises today are driven to improve responsiveness to customers and events, an objective commonly sought through usage of a computing infrastructure that attains access to integrated, real-time information. One aspect of real-time enterprises is a capability to materialize data from disjointed databases into an integrated data model. Many problems, such as synchronization of master data, cannot be solved effectively by a federated database approach alone. Data elements are deduplicated and merged into a common data model to create a semantic bridge between systems. Existing tools and methods operate in batch mode to support business intelligence applications, but little is available to support real-time information integration.
Latency, an inability to react immediately to business stimuli, can contribute to basically any deficiency in business performance, for example poor customer service, missed selling opportunities, failure to address consumer fraud, insufficiency in monitoring enterprise finances, and the like. A zero latency enterprise (ZLE) performance has been sought to enable enterprises to eliminate latency from operations so that business events that occur anywhere in an organization can immediately trigger appropriate actions across other parts of the enterprise and beyond. Elimination of operational inconsistency is sought to enable users to gain real-time consolidated performance and enable the enterprise to become more responsive and competitive.
The challenge is attaining a zero latency performance so that a business can integrate, synchronize, and route data a cross the enterprise, all in real time.
One technique that has been attempted to attain a low latency performance relies on standard applications to supply data services using a standard data model. Another technique attempts to customize a data model without recoding applications through usage of table-driven code. Table-driven code is deficient in capability to handle new data cases well if the new cases have attributes unlike previous cases. Another attempted solution is usage of user-exits to evade limitations of table-driven approaches. User-exits are difficult to integrate into the application, as data and functions available to user-exits are typically very limited.
While many industry participants have sought real-time performance, few have attained more than simple asynchronous message passing middleware. Similarly, an adaptive computing capability has been discussed but not progressed beyond simple system level concepts such as computing on demand.